Szczegóły publikacji
Opis bibliograficzny
Automatic prostate segmentation in MR images based on 3D active contours with shape constraints / Andrzej SKALSKI, Jakub Łągwa, Tomasz ZIELIŃSKI, Piotr Kedzierawski, Tomasz Kuszewski // W: SPA 2013 : Signal Processing : Algorithms, Architectures, Arrangements, and Applications : Poznań, 26–28th September 2013 : conference proceedings / IEEE The Institute of Electrical and Electronics Engineers Inc. Region 8 – Europe, Middle East and Africa. Poland Section. Chapters Signal Processing, Circuits and Systems, Poznań University of Technology. Faculty of Computing. Chair of Control and System Engineering. Division of Signal Processing and Electronic Systems. — Poznań : PUT, [2013]. — ISBN: 978-83-62065-15-8; e-ISBN: 978-83-62065-17-2. — S. 246–249. — Bibliogr. s. 249, Abstr.
Autorzy (5)
- AGHSkalski Andrzej
- AGHŁągwa Jakub
- AGHZieliński Tomasz
- Kędzierawski Piotr
- Kuszewski Tomasz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 76387 |
|---|---|
| Data dodania do BaDAP | 2013-10-07 |
| Rok publikacji | 2013 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | Signal Processing Algorithms, Architectures, Arrangements, and Applications 2013 |
Abstract
Planning radiotherapy of prostate cancer requires the prostate segmentation in computed tomography (CT) images that can be manual (done by medical doctors), semi-automatic or automatic. Additional usage of magnetic resonance (MR) images, where the soft tissue are better visible, makes this operation more robust. The paper addresses the problem of prostate segmentation in MR data. Its main contribution relies on novel application of the well-known active contour (AC) method with gradient vector flow (GVF) modification to this task. It is shown in the paper that such approach is successful only after addition of a priori knowledge in the form of prostate shape constraint. The statistical prostate shape was modeled as an ellipse which parameters are calculated exploiting statistical atlas principles. It is presented using Dice similarity measure that the proposed automatic prostate segmentation offers results that are very close to the manual ones and can be used in radiotherapy planning.
